Amazon Aurora is a relational database engine. It is designed to deliver the speed and reliability of high-end commercial databases in a simple and cost-effective manner. Amazon claims that it delivers up to five times the throughput of standard MySQL running on the same hardware. If you’re already using MySQL software for your database like a huge majority of people, Aurora is compatible with MySQL 5.6. This means that your existing MySQL applications and tools can still run on Aurora with no modification required.
Database engines available to RDS users
Firstly, Amazon’s RDS is a tool that handles provisioning, patching, backup, recovery, failure detection and repair of your relational database. This leaves you with more time to concentrate on your data. There are currently six database engines available to RDS users. These are Amazon Aurora, MySQL, Oracle, Microsoft SQL Server, PostgreSQL and MariaDB.
When people think databases a lot of them automatically think MySQL or PostgreSQL. How does Amazon Aurora compare to these two heavyweights and why choose it when MySQL and PostgreSQL are both compatible with RDS?
The benefits of choosing Aurora
Well, it turns out that there may be some considerable benefits for choosing Aurora over either of the two. Comparing Aurora to MySQL or PostgreSQL can be thought of as comparing a cloud model to a traditional model in many ways. Aurora has characteristics such as elasticity and scalability which are always associated with the cloud while the more traditional counterparts, give the user more control of how the database is deployed, maintained and ran even if they are run with RDS which is a cloud based concept of service delivery itself.
With that being said Amazon claims to have some very decent measures put in place to ensure that Aurora suffers no breakdowns or problems around the clock. Firstly you can create up to 15 replicas, which increases throughput and is more than enough failover targets. These replicas share storage with the primary instance which almost eliminates the lag in replication (reports of a tiny lag, around 10-20 milliseconds due to page caching in the replicas). According to amazon recovery from physical storage failures is transparent and it usually takes less than a minute for an instance to restart.
Built in high availability comes as standard, data is replicated to 3 availability zones, with two copies of data in each zone. These measures are designed to give Aurora greater than 99.99% availability, and also data is backed up continuously to Amazon S3. Aurora’s availability, scalability, and durability are advantages over MySQL RDS and PostgreSQL. You could even say Aurora increases MySQL performance and availability as the Aurora database engine is closely integrated with an SSD-backed virtualized storage layer which is designed for database workloads.With MySQL and PostgreSQL with RDS you can choose from General Purpose (SSD) storage, Provisioned IOPS (SSD) storage, or magnetic storage.
Planning disk usage
A common nuisance for traditional database users is always planning for disk usage. The consequences can be quite serious if the estimation has been overshot, wasting money on unused resources and also if it has been undershot, meaning running out of storage space. Aurora databases, however, use Amazon S3 for storage rather than normal disks, this makes auroras storage very elastic.
If you require a highly scalable, reliable and efficient database and you are willing to trust AWS to provide you with the tools and resources to do so look no further.
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